Machine Learning Used for DevOps with Sumo Logic

To start out with, the guys from Sumo Logic dreamed of a world of Yottabyte scale data where machine learning algorithms were able to make sense of it all. Today they are moving through the enterprise world in petabytes to get there.

The amount of log data bulging and swirling around infrastructure systems, let alone business data, can make it challenging and time consuming for engineers to identify pain points and expedite remedial action.

Sumo Logic is fast growing in popularity, not only as a way of aggregating data across complex distributed systems but also to allow administrators to filter log data using Sumo Logic’s LogReduce™ Technology which reduces events into groups of patterns and ultimately saves time.

Using Machine Learning algorithms Sumo Logic is able to identify deviations in data patterns from previous logs to enable Administrators to jump on any areas of concern in an instant and as with all machine learning algorithms, users can train it to improve subsequent performance all from a customisable dashboard which enables users to drive customisable alerts.

The tool allows companies to easily understand how customers interact with their business and for transactional websites see where any bottlenecks occur against set parameters and how to resolve them in order to pass checks.

 

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About Gary Donovan

Machine Learning and Data Science blogger, hacker, consultant living in Melbourne, Australia. Passionate about the people and communities that drive forward the evolution of technology.
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